Lamissi is a New Zealand restaurant and our first client. We built and launched its website on Velora — our managed platform for online ordering, bookings and payments — and set it up so AI assistants can read the menu, hours and location as easily as a customer can.
Lamissi launched on Velora, our fully managed restaurant platform. Rather than a brochure site with a PDF menu, the whole thing is built around the order.
Menu, cart, checkout and table bookings on one site, with Stripe handling payments.
The restaurant manages the menu, prices, opening hours and orders themselves — no developer in the loop.
Built for the phone first, because that is where nearly three-quarters of the visits come from.
Hosting, updates, uptime and changes are handled by Codifyany on the Velora platform.
Traffic figures are from Vercel Analytics for the most recent three-month period, compared with the three months before it. The booking figures come from the reservation system on the site itself. Neither includes order revenue, which sits in the restaurant's own systems.
confirmed table bookings for 165 guests over the last three months
Of 60 requests in the window: 47 confirmed, 11 cancelled by the guest, 1 declined, 1 still pending — each one approved or declined by the restaurant from the same admin dashboard they use for the menu.
Velora bookings · last 3 monthsAsk ChatGPT for Sri Lankan restaurants around Auckland and Lamissi is in the shortlist. Ask Google in AI Mode and it returns a full card — 4.6 stars, price range, and the Friday hopper station and weekend lamprais pulled straight from the site's own structured data. A year ago there was nothing for those systems to read; now the restaurant is one of the names they hand back.
Around 1,800 visits in the quarter came from Google (google.com and google.co.nz), far ahead of every other source. Organic discovery is doing the work — the site is being found by people searching, not just people who already knew the name.
After the homepage, the two most-visited pages are the menu (~1,100 visitors) and the order page (~940). Stripe Checkout also shows up in the referrer list, which confirms orders are being placed. The site is doing the one job it was built for.
73% of visits are on a phone and 91% are from New Zealand. That is the traffic profile of a neighbourhood restaurant, and it is what the mobile-first design and local structured data are built around.
Visitors and page views are both up more than half on the previous quarter, spread across the whole period rather than one campaign burst — the pattern you want from an owned channel.
Table reservations come in through the site and the restaurant approves or declines each one from the admin dashboard — no phone tag, no paper diary. Last quarter that turned 60 requests into 47 confirmed bookings for 165 guests.
When someone asks ChatGPT, Google's AI Overview or Perplexity "where can I get Sri Lankan food near me?", those systems can only recommend a place they can actually read. Lamissi's site carries structured data for the business, its location and opening hours, and its menu — so an assistant can pull the answer directly rather than guessing from a scanned image or a third-party listing.
The same work that makes the site easy for a person to use quickly — clear headings, a real menu in text, an obvious way to order — is what makes it easy for a machine to quote. This is the GEO approach applied to a small local business.
Velora gets you a site that takes orders and bookings, is managed for you, and is built so customers and AI assistants can both find you. Book a free call and we will show you how Lamissi is set up.